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Customize Amazon Textract with business-specific documents using Custom Queries

AWS Machine Learning

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. Queries is a feature that enables you to extract specific pieces of information from varying, complex documents using natural language. personal or cashier’s checks), financial institution and country (e.g.,

APIs 97
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Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

AWS Machine Learning

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Extract and analyze data from documents.

Scripts 71
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Automate document validation and fraud detection in the mortgage underwriting process using AWS AI services: Part 1

AWS Machine Learning

In this three-part series, we present a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Fraudsters range from blundering novices to near-perfect masters when creating fraudulent loan application documents.

APIs 69
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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We discussed how we can use AWS AI services to accurately categorize claims documents along with supporting documents. Part 1: Classification and extraction of documents.

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Study: The Health of the Contact Center

What does it take to engage agents in this customer-centric era? Download our study of 1,000 contact center agents in the US and UK to find out what major challenges are facing contact center agents today – and what your company can do about it.

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Using Customer Satisfaction Metrics: NPS Best Practices

Totango

Luckily, there’s a measure for that, too: customer satisfaction metrics. Therefore, you should not only track customer satisfaction, but you should also empower your customer success team to take action based on the lessons these metrics teach you, customer satisfaction metrics. . Document how long onboarding takes.

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Automated Customer Correspondence

Cincom

Yet with siloed data, scattered document creation processes, and constantly evolving regulatory policies, even the most well-intentioned businesses struggle to deliver timely, compliant, and impactful correspondence. Manual document creation simply cannot keep pace. Data from multiple backends like CRM, ERP, policy systems, etc.

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The Challenges of Omnichannel: Why so Many Contact Centers Struggle with Digital Self-Service

To find how contact centers are navigating the transition to omnichannel customer service, Calabrio surveyed more than 1,000 marketing and customer experience leaders in the U.S. about their digital customer communication strategies. Read the report to find out what was uncovered.

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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.